Search Results (245)

Background/Objectives: This quantitative cross-sectional study examined the relationships between self-efficacy, compassion fatigue, and the quality of nursing work life (QNWL) in primary care nurses from the Dammam and Riyadh regions of Saudi Arabia. This study examined how these factors varied according to gender, education, income, and years of experience. Methods: A total of 158 primary care nurses completed validated survey instruments, including the General Self-Efficacy Scale, Professional Quality of Life Scale—Version 5, and Work-Related Quality of Life Scale-2. Descriptive statistics were used for data analysis. Results: The results indicated that participants experienced elevated self-efficacy (M = 29.53, SD = 0.52), moderate compassion fatigue (M = 54.62, SD = 10.16), and moderate overall quality of work life (QWL) (M = 3.26, SD = 0.52). Positive correlations were identified between self-efficacy and QWL (r = 0.250, p < 0.05) and compassion satisfaction (r = 0.533, p < 0.05). By contrast, compassion fatigue was negatively correlated with QWL (r = −0.259, p < 0.05). Notable disparities in QWL were identified according to education level and years of experience, with nurses possessing advanced degrees and those with less experience having elevated QNWL scores. Conclusions: This study highlights the significance of promoting self-efficacy and mitigating compassion fatigue to improve the quality of nursing. Administrators and nurse leaders should consider strategies such as continuous professional development, psychological support, and effective workload management to enhance the well-being and retention of primary care nurses. Full article

The number of people requiring palliative care is increasing. This can result in moral and ethical conflicts that may lead to psychological distress and moral injury. (MI). Solutions are needed to counteract career abandonment—supervision (SV) could be one solution. This study examines the extent to which palliative care nurses link MI to their everyday experiences and whether SV can contribute to the identification and prevention of moral distress and MI. In addition, factors that influence the implementation of, participation in, and perception of SV are analyzed. A qualitative study design was chosen for the investigation, consisting of guided interviews, narrative-generating questions with seven participants working in palliative care, and participant observation with audio recording during two supervisions of two palliative care teams with 16 participants in total. The data was analyzed using qualitative content analysis according to Mayring. The results show differences in workload between acute and palliative care wards. Time pressure and hierarchical structures promote distress and MI and are particularly evident on acute wards. The interviewees described specific experiences of MI. In addition, factors were identified that influence participation in SV. The analysis of SV showed that workload is a key cause of moral distress and can have an impact on health. SV can be used for sensitization and exchange. Implementation and acceptance of SV depend on individual and structural factors. In palliative care, signs of moral distress are present and are specifically addressed in SV, which means that SV can be a tool for dealing with stressful situations. Full article

Background: Nursing students often experience heightened levels of stress during clinical training due to the dual demands of academic and clinical responsibilities. These stressors, compounded by environmental and organizational factors, can adversely affect students’ well-being, academic performance, and the quality of patient care they deliver. Aim: This study aimed to identify the key stressors influencing nursing students’ perceptions of single-shift quality (SSQ) during clinical training and to examine how well students can predict the quality of their shift based on pre-shift expectations. Methodology: A cross-sectional survey design was implemented, collecting pre- and post-shift data from 325 nursing students undergoing clinical training in Alabama. The survey measured 13 domains related to workload, environmental conditions, organizational interactions, coping strategies, and overall satisfaction. Paired t tests and linear regressions were used to assess changes in perception and identify key predictors of SSQ. Results: This study found significant discrepancies between students’ pre- and post-shift evaluations across multiple domains, including internal environment, organizational interaction with clinical faculty/preceptors, and coping strategies (p < 0.001). Students also accurately predicted stable factors such as patient characteristics and external environment. Pre-shift expectations did not significantly predict post-shift experiences. Post-shift perceptions revealed that stress-coping strategies and collegiality were the strongest predictors of shift quality. Conclusion: Students enter clinical shifts with optimistic expectations that often do not align with actual experiences, particularly regarding support and stress management. The SSQ framework offers a valuable tool for identifying gaps in clinical training and guiding interventions that foster resilience and better alignment between expectations and real-world practice. Full article

The adjuvant treatment landscape for hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2–) early breast cancer (EBC) is rapidly evolving, with a diverse range of therapeutic options—including endocrine therapies, bisphosphonates, ovarian function suppression, olaparib, CDK4/6 inhibitors, and emerging agents such as immunotherapy. While these advances have markedly improved patient outcomes, they also introduce challenges related to implementation, monitoring, and resource allocation. Notably, therapies like CDK4/6 inhibitors require particularly close monitoring, creating logistical and capacity challenges for medical oncologists, whose workloads are already stretched due to rising cancer incidence and treatment complexities. These challenges underscore the need for innovative care delivery solutions to ensure patients with EBC continue to receive optimal care. This paper offers a comprehensive guide—a playbook—of multidisciplinary-team-based care models designed to optimize adjuvant treatment delivery in EBC. Drawing on real-world evidence and successful applications across Canadian centers, we explore models led by nurses, nurse practitioners (NPs), general practitioners in oncology (GPO), and pharmacists. Each model leverages the unique expertise of its team to manage treatment toxicities, facilitate adherence, and enhance patient education, thereby promoting effective and sustainable care delivery. Importantly, these models are not intended to compete with one another, but rather to serve as a flexible recipe book from which breast cancer care teams can draw strategies tailored to their local resources and patient needs. By detailing implementation strategies, benefits, and challenges—in many instances supported by quantitative metrics and economic evaluations—this work aims to inspire care teams nationwide to optimize the adjuvant management of patients with HR+, HER2– EBC. Full article

Background/Objectives: Nursing staff face mentally and physically demanding work environments in the obstetrics and gynecology departments in hospitals. This study elucidated the working hours of midwives and nurses in these departments and the background factors influencing them. Methods: This study employed a quantitative, descriptive, and correlational cross-sectional design. A questionnaire-based survey targeting nursing personnel working in the obstetrics and gynecology departments in hospitals across Japan was conducted. The respondents’ attributes, working hours, number of night shifts, and other employment conditions were described. To identify the background factors of long working hours, multivariate logistic regression analysis was performed using working hours ≥50 h per week as dependent variables and respondents’ attributes and employment conditions as explanatory variables. Results: Questionnaires were sent to 1170 hospitals, and valid responses were obtained from 2043 nursing personnel in 474 hospitals. Working ≥50 and ≥60 h per week were observed in 15.5% and 3.6% of the respondents, respectively, and 54.2% reported working night shifts ≥5 times monthly. Background factors strongly correlated with working ≥50 h per week among nursing staff included being in their 40s, licensed practical nurses, or a head nurse; having 5–8 night shifts per month; and working in hospitals with a total bed count of 200–400, 400–600, or 600–800, as well as ≥10 full-time physicians, ≥10 or an unknown number of advanced practice midwives, and >400 inpatient midwifery delivery cases annually. Conclusions: Urgent interventions are needed to reduce the workload of nursing staff in the obstetrics and gynecology departments of Japanese hospitals. Full article

The COVID-19 pandemic has led to a general increase in the workload in Intensive Care Units (ICUs). The objective here was to analyze the nursing workload in a Cardiology ICU of a tertiary and teaching inner hospital in Brazil before and during the COVID-19 pandemic. A retrospective and ecological study was conducted. Nursing Activities Score mean by month (NAS-mm) data were collected from the unit’s opening in October 2014 until May 2023. The data were divided into pre-pandemic and pandemic periods, with the pandemic further divided into three phases/years. A workload decrease was observed during the pandemic and varied across different pandemic years. In the pre-pandemic period, the mean was 53.80 points (95%CI: 52.99; 54.60; n = 65), whereas during the pandemic, it was 52.02 points (95%CI: 50.88; 53.17; n = 39). The first year had the lowest mean workload at 50.94 points, followed by the second year with 48.37 points, while the third year had the highest with 55.82 points, exceeding the pre-pandemic period’s workload. Amid the COVID-19 pandemic scenario, a decrease in nursing workload was observed in the unit, only returning to reference values in the third pandemic year, possibly associated with patient and administrative profile changes. Full article

Background/Objectives: Nursing diagnosis is a complex process that requires clinical judgment, time, and resources and whose implementation is hindered by factors such as workload, lack of time, and resistance to computerized systems. This study aimed to compare the quality and efficiency of care plans generated by nursing professionals versus those produced by an artificial intelligence (AI) model, using the NANDA, NOC, and NIC taxonomies as criteria. Methods: An observational study was carried out with three simulated clinical cases. Thirty experts, fifty-four nursing professionals, and the ChatGPT model (GPT-4) were included. The experts established the referral plans using the Delphi technique. Responses were evaluated with a validated rubric (EADE-2) and analyzed using nonparametric tests. Professionals’ perceptions on the use of computer systems were also collected. Results: ChatGPT scored significantly higher on several dimensions (p < 0.001) and resolved all three cases in 35 s, compared to an average of 30 min for practitioners. Professionals expressed dissatisfaction with current diagnostic documentation systems. Conclusions: AI demonstrates high potential in optimizing the diagnostic process in nursing, although for its implementation human supervision, ethical aspects and improvements in current systems must be considered to achieve effective integration. Full article

Fatigue among hospital nurses, resulting from demanding workloads and irregular shift schedules, presents significant risks to both healthcare workers and patient safety. This study developed a fatigue detection model using heart-rate variability (HRV) and investigated its relationship with the Swedish Occupational Fatigue Inventory (SOFI) among nurses. Sixty nurses from a hospital in Depok, Indonesia, participated with HRV data collected via Polar H10 monitors before and after shifts alongside SOFI questionnaires. A mixed ANOVA revealed no significant between-subjects differences in HRV across morning, afternoon, and night shifts. However, within-subjects analyses showed pronounced parasympathetic rebound (elevated Mean RR) and sympathetic withdrawal (reduced Mean HR) post-shift, particularly after afternoon and night shifts, contrasting with stable profiles in morning shifts. Correlation analysis showed significant associations between SOFI dimensions, specifically lack of motivation and sleepiness, with HRV measures, indicating autonomic dysfunction and elevated stress levels. Several machine-learning classifiers were used to develop a fatigue detection model and compare their accuracy. The Fine Gaussian Support Vector Machine (SVM) model achieved the highest performance with 81.48% accuracy and an 81% F1 score, outperforming other models. These findings suggest that HRV-based fatigue detection integrated with machine learning provides a promising approach for continuous nurse fatigue monitoring. Full article

Background: The quality of palliative care (PC) services is closely linked to the effectiveness of interdisciplinary collaboration. A coordinated approach among professionals from different fields fosters holistic, person-centered care, ensuring comprehensive support for patients with complex conditions and their families. In hospital settings, In-Hospital Palliative Care Support Teams (EIHSCPs) play a key role in delivering specialized care, enhancing interdepartmental communication, training other healthcare professionals, and optimizing resources. Strong leadership by PC specialists, combined with effective team management, contributes to symptom relief, improved quality of life, and cost reduction. However, interdisciplinary collaboration presents challenges, including competing priorities, resource constraints, and communication barriers. Despite its recognized benefits, research on its implementation in PC, particularly in Portugal, remains scarce. Objective: This study explores the perspectives and practices of professionals within an EIHSCP, examining team dynamics, interprofessional collaboration, and key facilitators and barriers. Methods: Twelve semi-structured interviews were conducted with physicians, nurses, psychologists, and social workers from the EIHSCP in the Médio Tejo region. Data were analyzed using Braun and Clarke’s reflexive thematic analysis. Results: The interview findings were organized into three themes: (1) Social Representations and Interdisciplinary Practice; (2) Competencies for Interdisciplinary Practice; and (3) Challenges in Interdisciplinary Practice. Participants consistently highlighted that interdisciplinary collaboration enhances communication between services and improves care quality. While teamwork is central, patient- and family-centered care remains the priority. Key competencies include empathy, ethics, active listening, and cultural sensitivity, alongside structural and procedural elements such as team meetings, integrated communication, and clear referral criteria. Continuous education and professional development are essential. Challenges primarily stem from limited human and material resources, staff workload and stress, communication gaps between hospital and community teams, and insufficient institutional recognition. Suggested improvements focus on investing in ongoing training, strengthening communication and inter-institutional collaboration, and revising the organizational model of PC within Portugal’s National Health Service. Conclusions: Interdisciplinary collaboration in PC is fundamental for holistic, patient-centered care but is hindered by structural and organizational barriers. Full article

Background/Objectives: Performing cardiopulmonary resuscitation (CPR) is cognitively demanding, often requiring helpers to perform cognitive and manual tasks simultaneously. While the human brain primarily switches between tasks rather than processing them simultaneously, it remains unclear whether performing repetitive, monotonous manual tasks, such as chest compressions, affects cognitive performance. This study aimed to assess the impact of chest compressions on mental arithmetic performance. Methods: In a randomized crossover trial, healthy participants trained in advanced life support (physicians, nurses, and paramedics) completed the Paced Auditory Serial Addition Test (PASAT) under two conditions: with or without performing chest compressions on a manikin. The primary outcome was the number of correct PASAT answers. Secondary outcomes included workload assessment using the NASA Task Load Index (TLX) and chest compression (CC) performance. The trial was registered at clinicaltrials.gov and approved by the local ethics committee. Results: Thirty-eight participants were included. The number of correct PASAT responses was significantly lower during chest compressions compared to the control (36.5 vs. 41; p < 0.01). NASA TLX values were significantly higher in the chest compression condition, indicating increased perceived workload. Chest compression performance showed statistically significant differences between a phase of just chest compressions and during the PASAT, especially increased levels of incomplete recoil. Conclusions: This study demonstrates that even a simple repetitive motor task like chest compressions impairs cognitive task performance significantly. Furthermore, multitasking was shown to decrease chest compression quality. These findings strongly highlight the importance of effective task allocation and minimizing multitasking during CPR to optimize performance and thereby patient outcomes. Full article

Background/Objective: Part of the workload of ambulance service involves patients with low-acuity health events that do not require the specific resources provided by ambulance services or emergency departments (EDs). The problem of inappropriateness is also present in Italy. However, research is limited to the perspective of triage nurses only, excluding patients and emergency medical service (EMS) staff. This study aims to identify the presence of inappropriate ambulance use in the study context by comparing patients’ perception of emergency with appropriateness perspectives of both triage nurses and emergency service staff. Methods: A cross-sectional study involving 109 patients transported by ambulance was performed between January and March 2020. Questionnaires were distributed to patients, EMS staff, and triage nurses operating in the chief town and hinterland of a region of Italy. Results: Non-penetrating trauma was the most frequent cause for calling an ambulance. Patients referred that activation of the service was necessary, while triage nurses and EMS technicians were in line in believing the non-urgency of the call due to non-emergent health conditions. Conclusions: Although we cannot conclude that citizens use the emergency system inappropriately, the results of this study make us think about the need to implement educational interventions that increase citizens’ knowledge of how the service works and the territorial services available. Full article

Background/Objetives: Pressure injuries pose a significant challenge in healthcare, adversely impacting individuals’ quality of life and healthcare systems, particularly in intensive care units. The effective identification of at-risk individuals is crucial, but traditional scales have limitations, prompting the development of new tools. Artificial intelligence offers a promising approach to identifying and preventing pressure injuries in critical care settings. This review aimed to assess the extent of the literature regarding the use of artificial intelligence technologies in the prediction of pressure injuries in critically ill patients in intensive care units to identify gaps in current knowledge and direct future research. Methods: The review followed the Joanna Briggs Institute’s methodology for scoping reviews, and the study protocol was prospectively registered on the Open Science Framework platform. Results: This review included 14 studies, primarily highlighting the use of machine learning models trained on electronic health records data for predicting pressure injuries. Between 6 and 86 variables were used to train these models. Only two studies reported the clinical deployment of these models, reporting results such as reduced nursing workload, decreased prevalence of hospital-acquired pressure injuries, and decreased intensive care unit length of stay. Conclusions: Artificial intelligence technologies present themselves as a dynamic and innovative approach, with the ability to identify risk factors and predict pressure injuries effectively and promptly. This review synthesizes information about the use of these technologies and guides future directions and motivations. Full article

Enhancing maternal and newborn care is a key priority for governments worldwide. World leaders have taken deliberate steps to improve these essential services, with an emphasis on postnatal care, including home visits for mothers and their newborns. However, in the Ashanti Region and across Ghana, challenges surrounding the delivery and effectiveness of postnatal home visits remain a significant concern. This study aimed to assess the attitudes of Community Health Nurses towards postnatal home visitation in selected districts of the Ashanti Region. A quantitative survey approach was used to gather data from 100 CHNs randomly selected from 10 regional districts. Structured questionnaires were used to gather quantitative data from CHNs. Findings from the study were analysed using descriptive and inferential tests. The study results indicated that most of the CHNs were young adults, 35 years of age (79%), with the majority having 3–5 years of work experience. The respondents generally demonstrated a negative attitude towards PNHV as they believed it was an extra workload, time-consuming, and unnecessary. A Pearson chi-square test indicated strong significant association between CHNs’ attitude towards the components of the attitude scale and years of experience as well as their age. In conclusion, the study revealed that even though CHNs are expected, as part of their job description, to embark on home visitation activities, most of them have a negative attitude towards this professional duty. There should be conscientious, novel ways to ignite the interest of these essential service providers to help improve infant and maternal health. Full article

(1) Background: The enduring impact of COVID-19 on the long-term care (LTC) sector remains uncertain, necessitating targeted efforts to address current and emerging challenges. This study aims to identify the key stressors faced by healthcare workers (HCWs) in LTC and to co-develop innovative, actionable strategies that mitigate these stressors, foster resilience, and promote workforce retention. (2) Methods: This study utilized a qualitative co-design methodology within a mixed-methods, multi-phase framework conducted between July 2023 and October 2024. This article focuses on Phase 1, which involved 11 semi-structured focus groups and steering group discussions with 24 HCWs, including personal support workers (PSWs), nurses, and LTC administrators across Ontario to explore workplace-related distress and foster a shared understanding of challenges in the LTC sector. Data were audio-recorded, transcribed verbatim, and analyzed using thematic analysis to derive key themes and actionable insights. (3) Results: Key themes emerging from co-design sessions included the need for (i) effective workload management tools, (ii) the prioritization of psychological safety and mental health services, (iii) reducing regulatory and bureaucratic burdens, (iv) strengthening management practices, and (v) fostering recognition and a positive sector image. Co-design sessions with HCWs and leaders facilitated the identification of priority issues and high-level solutions, including addressing workload issues, implementing mental health and support programs, enhancing work–life integration, improving management training, and promoting psychological safety in LTC settings. (4) Conclusions: This study deepens our understanding of workplace challenges in the LTC sector and the factors contributing to HCWs’ mental distress. Leveraging a co-design approach offers valuable insights into the lived experiences of HCWs and leaders. The findings provide actionable guidance for LTC leaders and policymakers to create effective, tailored interventions that actively engage HCWs in addressing workplace stressors and mitigating recurrent challenges. Full article

Effective crew scheduling in hospitals with multiple personnel groups is essential for time efficiency and fair workload distribution. This study focuses on optimizing shift scheduling for a team of nurses, doctors, and caregivers working in the Pediatric Intensive Care Unit (PICU) of a university hospital. The model is implemented and solved using GAMS 23.5 software to minimize total staffing costs while ensuring balanced shift allocations. The scheduling process in PICUs is influenced by multiple factors, including staff skills, experience levels, personal preferences, contractual agreements, and hospital demands. Since these factors affect doctors, nurses, and caregivers differently, the model considers each personnel group separately while integrating them into a unified optimization framework. The proposed model successfully generates an annual optimal shift schedule for 10 doctors, 14 nurses, and 9 caregivers, ensuring equitable workload distribution and compliance with hospital regulations. By implementing this scheduling approach, employee satisfaction is enhanced, service quality is improved, and administrative workload is reduced. Additionally, the model ensures a well-balanced distribution of responsibilities, minimizes scheduling inefficiencies, and significantly reduces the time required for shift planning. Ultimately, this study provides a fast, fair, and cost-effective solution for hospital workforce management. Full article